Giang Amanda, Edwards Morgan R, Fletcher Sarah M, Gardner-Frolick Rivkah, Gryba Rowenna, Mathias Jean-Denis, Venier-Cambron Camille, Anderies John M, Berglund Emily, Carley Sanya, Erickson Jacob Shimkus, Grubert Emily, Hadjimichael Antonia, Hill Jason, Mayfield Erin, Nock Destenie, Pikok Kimberly Kivvaq, Saari Rebecca K, Samudio Lezcano Mateo, Siddiqi Afreen, Skerker Jennifer B, Tessum Christopher W
Institute for Resources, Environment and Sustainability, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
Department of Mechanical Engineering, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
Proc Natl Acad Sci U S A. 2024 Mar 26;121(13):e2215688121. doi: 10.1073/pnas.2215688121. Epub 2024 Mar 18.
Equity is core to sustainability, but current interventions to enhance sustainability often fall short in adequately addressing this linkage. Models are important tools for informing action, and their development and use present opportunities to center equity in process and outcomes. This Perspective highlights progress in integrating equity into systems modeling in sustainability science, as well as key challenges, tensions, and future directions. We present a conceptual framework for equity in systems modeling, focused on its distributional, procedural, and recognitional dimensions. We discuss examples of how modelers engage with these different dimensions throughout the modeling process and from across a range of modeling approaches and topics, including water resources, energy systems, air quality, and conservation. Synthesizing across these examples, we identify significant advances in enhancing procedural and recognitional equity by reframing models as tools to explore pluralism in worldviews and knowledge systems; enabling models to better represent distributional inequity through new computational techniques and data sources; investigating the dynamics that can drive inequities by linking different modeling approaches; and developing more nuanced metrics for assessing equity outcomes. We also identify important future directions, such as an increased focus on using models to identify pathways to transform underlying conditions that lead to inequities and move toward desired futures. By looking at examples across the diverse fields within sustainability science, we argue that there are valuable opportunities for mutual learning on how to use models more effectively as tools to support sustainable and equitable futures.
公平是可持续性的核心，但当前为增强可持续性而采取的干预措施往往在充分解决这种联系方面有所欠缺。模型是指导行动的重要工具，其开发和使用为在过程和结果中以公平为核心提供了机会。本观点强调了在可持续性科学中将公平纳入系统建模方面取得的进展，以及关键挑战、矛盾和未来方向。我们提出了一个系统建模中公平的概念框架，重点关注其分配、程序和认知维度。我们讨论了建模者在整个建模过程中以及从一系列建模方法和主题（包括水资源、能源系统、空气质量和保护）中如何与这些不同维度互动的例子。综合这些例子，我们确定了通过将模型重新构建为探索世界观和知识系统多元性的工具来增强程序公平和认知公平方面的重大进展；通过新的计算技术和数据源使模型更好地体现分配不公平；通过将不同建模方法联系起来研究可能导致不公平的动态；以及开发更细致入微的指标来评估公平结果。我们还确定了重要的未来方向，例如更加注重使用模型来确定转变导致不公平的潜在条件并迈向理想未来的途径。通过审视可持续性科学中不同领域的例子，我们认为在如何更有效地将模型用作支持可持续和公平未来的工具方面存在相互学习的宝贵机会。
